In wireless communication systems, there is a constant strive for improvement of transmission technologies in order to utilize the available spectrum in most efficient way.
Multiple-input Multiple-Output (MIMO) technology is one such effort to improve communication performance. In MIMO, use is made of multiple antennas at both the transmitter and receiver, thereby enabling increased data throughput and coverage without additional spectrum or increased transmission power. The transmitter thus sends multiple streams by multiple transmit antennas and the transmitted streams are received by the multiple antennas of the receiver.
The receiver may decode the streams by using a linear demodulation method, such as minimum mean square error (MMSE) estimation. However, with access to more computational power more advanced receiver structures can be used in order to improve the transmission speed and/or noise robustness of the wireless MIMO receivers. For example, a non-linear demodulation method may be used, such as Joint Demodulation (JD), also denoted Maximum Likelihood (ML) detection, which selects the most probable combinations of transmitted signals.
To fully take advantage of the increased performance of such non-linear demodulation, proper link adaptation methods are required. Otherwise a sub-optimal choice of modulation and coding may be done, leading to lower performance than the ML-detector is actually capable of. In the 3GPP Long Term Evolution (LTE), link adaptation is based on measured instantaneous Signal to Interference and Noise Ratio (SINR). The SINR is used for selecting modulation and coding scheme (MCS) for transmissions.
For the linear MMSE receiver, there exists well-known expressions for the SINR estimation, but for a non-linear joint demodulation it is not as straight-forward to calculate the SINR estimate. One known way is to add a certain offset to the MMSE-based estimate, which will slightly increase the performance.
Another suggested way is to use soft values at the output of the ML detector in order to estimate the channel quality.